The present disclosure relates generally to presentation of audio at a headset, and specifically relates to determination of acoustic parameters for a headset using a mapping server.
A sound perceived at the ears of two users can be different, depending on a direction and a location of a sound source with respect to each user as well as on the surroundings of a room in which the sound is perceived. Humans can determine a location of the sound source by comparing the sound perceived at each set of ears. In an artificial reality environment, simulating sound propagation from an object to a listener may use knowledge about the acoustic parameters of the room, for example a reverberation time or the direction of incidence of the strongest early reflections. One technique for determining the acoustic parameters of a room includes placing a loudspeaker in a desired source location, playing a controlled test signal, and de-convolving the test signal from what is recorded at a listener location. However, such a technique generally requires a measurement laboratory or dedicated equipment in-situ.
To seamlessly place a virtual sound source in an environment, sound signals to each ear are determined based on sound propagation paths from the source, through an environment, to a listener (receiver). Various sound propagation paths can be represented based on a set of frequency dependent acoustic parameters used at a headset for presenting audio content to the receiver (user of the headset). A set of frequency dependent acoustic parameters is typically unique for a specific acoustic configuration of a local environment (room) that has a unique acoustic property. However, storing and updating various sets of acoustic parameters at the headset for all possible acoustic configurations of the local environment is impractical. Various sound propagation paths within a room between a source and a receiver represent a room impulse response, which depends on specific locations of the source and receiver. It is however memory intensive to store measured or simulated room impulse responses for a dense network of all possible source and receiver locations in a space, or even a relatively small subset of the most common arrangements. Therefore, determination of a room impulse response in real-time is computationally intensive as the required accuracy increases.